We examined the self reported morbidities among self and family members in construction workers and the potential economic impact in terms of CHE, i.e. medical expenses of more than 10% of annual family income. About one-third of the study population reported illness in the past year, and we identified important demographic and work-related determinants associated with those reported illnesses. About a quarter of the population reporting illness suffered CHE. Both the groups that suffered CHE and that did not, displayed similar trends in health-seeking behaviors.
The prevalence of self reported illnesses in the current study is consistent with the global profile but higher than the Indian profile. An Iranian study specific to construction workers reported 30% of injuries and 30–53% of most common illnesses involving the skin, eye, and musculoskeletal disorders [14]. Our study corresponds with these numbers except for musculoskeletal disorders, whose prevalence was higher (53%) in the cited study. While this Iranian study assessed the prevalence of illnesses, we specifically assessed that which required a healthcare visit. Our study population might likely have had a significant proportion of musculoskeletal illnesses. However, they might be disregarded as innate to the job itself, and workers might not have sought specific treatment for them. Examining the Indian literature, there are prevalent findings of self-reported health among the elderly population and mental health disorders. As of date, no specific studies reported similar estimates for construction workers in India. Thus we took a stance to compare these numbers with the existing literature on the elderly population. Among the aging Indian population, poor health status was reported by 15–26% elderly [15, 16]. One study assessed the incidence of any disease and hospitalization among the Indian elderly which were 31% and 6% respectively [17]. Our study identified that about 37% required a healthcare visit last year in the sample of construction workers studied. Even when our population comprises primarily young adults, these numbers illustrate a higher prevalence of illness than the prevalence among the elderly, who would expectantly have a higher prevalence of self-reported illness.
Poor living conditions were primarily associated with the prevalence of illnesses. Factors like shared kitchens and unfavorable cooking fuel types indicate the critical contributions of poor socioeconomic status to disease burden apart from the construction sites' inherent hazards. This highlights the need for improving the living conditions among construction workers. Also, about 75% of migrant workers did not report any illness compared to the non-migrant population. Yet, 60/63 reporting CHE were migrant workers. This may be because the migratory population might have sought medical care only when severe and might not have visited the healthcare unless the disease is severe and disrupting daily life. Also, these severe illnesess would have been expensive to manage which explains the CHE.
Though the literature suggests more working hours would be associated with morbidity [18], we observed a reduction of odds in reporting illness while working more hours. One reason maybe morbidities associated with long work hours may be cumulative and expressed over the years. But more practically, this directs us to think working for more hours might not give the flexibility for the workers to visit a healthcare. This notion is corroborated by another finding on reasons for not seeking government care. The majority noted that time was unsuitable for visiting a healthcare. Workers should be educated about the round-the-clock medical services at government centers nearby which will aid them in visiting and seeking care even while out of their regular working hours.
The economic impact of medical expenses in terms of CHE was high in our study population. In Nepal, Iran, and China - neighboring and developing countries, the out-of-pocket expenditure on medical costs leading to CHE was 11–13% [19]. In this study, we reported about 27% reporting CHE. In absolute numbers, an average household of a construction worker spent 29,000 INR, during the previous 12 months on medical expenses. In households that suffered a CHE, this was around 92,000 INR compared to 6,500 INR in a household that did not incur CHE. A Malawian study estimated 1.3% CHE in their community. However, the authors considered CHE as more than 10% of annual expenditure. In comparison to this, and even when considering the threshold of > 10% of annual family income, our estimates of 27% CHE is relatively high [20]. A study from Nepal industrial workers reported 13% of CHE while considering spending more than 20% of annual family income while reporting that the majority sought private care for medical treatment [21]. We also observed the majority seeking medical care from private centers along similar lines. However, this did not contribute to CHE incurrence in our population. We observed similar trends among the CHE incurred and non-incurred. Both the groups sought private care. This seems to convey that this might not be the primary reason driving the CHE in our population. As CHE incurred population reported significantly lower family income, it is plausible that CHE hit the already impoverished group of workers. On the other hand, CHE can be the second hit in a marginalized low-income group pushing them further into poverty.
Merits of our study should be considered with its limitations. Firstly, identifying illness history in the past based on self-reports carries reporting bias. Nevertheless, we asked for specific situations requiring a healthcare visit that might be more easily remembered, unlike the self-reported illnesses. This, according to us, will be more vivid to recollect, thus capturing the morbidity profiles better than self-reported health measures. Also, we did not restrict the question to the responder but included illness in any of the family members. This broad perception of including family members’ health profile is in line with the recent literature expanding the conceptual model of occupational health to include family members[22]. This is an added strength to the study. Secondly, we assessed CHE in proportion to the income. We acknowledge the bias of this classification as such that people who have higher income will be more likely to cross the threshold with their ability to pay more and wanting to seek better facilities than those with lower income. However, our study group without CHE reported a higher average family income than the CHE-incurred group. So we presume this bias may not have affected the current study. Future studies should compare and contrast different CHE classifications to understand this better. Third, we did not separate out where the health expenditure was distributed. It is possible that surgical intervention or a chronic illness might have costed more than a minor ailment requiring healthcare visits. However, both would have been captured by the larger umbrella of "illness." Finally, we do not have a further breakup of what illnesses were encountered by the construction workers. Our study did not intend to capture more information as working with limited resources and limited time to increase participation compliance.